Advances in Artificial Rabbits Optimization: A Comprehensive Review

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dc.authorscopusidNazım Ağaoğlu / 59486384100
dc.authorwosidNazım Ağaoğlu / LUZ-8322-2024
dc.contributor.authorAnka, Ferzat
dc.contributor.authorAğaoğlu, Nazım
dc.contributor.authorNematzadeh, Sajjad
dc.contributor.authorTorkamanian afshar, Mahsa
dc.contributor.authorGharehchopogh, Farhad Soleimanian
dc.date.accessioned2025-04-16T19:27:09Z
dc.date.available2025-04-16T19:27:09Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Matematik Bölümü
dc.description.abstractThis study provides an in-depth review and analysis of the Artificial Rabbit Optimization (ARO) algorithm inspired by the survival strategies of rabbits. The ARO tries to find the global solution in the search space according to the rabbits’ detour foraging strategy and searches locally according to their random hiding structure. This algorithm has various advantages such as a simple structure, fast running model, easy adaptation feature, few parameters, independent mechanism in exploration and exploitation phases, transitions between phases with a specific mechanism, reasonable convergence rate, and property of escaping local optima. Therefore, it has been preferred by many researchers to solve various complex optimization problems. ARO-based studies have been published at prestigious international publishers such as Elsevier, Springer, MDPI, and IEEE since its launch in July 2022. The rates of studies in these publishers are 34%, 19%, 18%, and 15%, respectively. The remaining 14% includes papers published by other publishers. Besides, the cited studies on this algorithm are examined in four categories: Improved, hybrid, variants, and adapted. Research trends demonstrate that 27%, 31%, 9%, and 33% of ARO-based studies fall into these categories. © The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE) 2024.
dc.identifier.citationAnka, F., Agaoglu, N., Nematzadeh, S., Torkamanian-afshar, M., & Gharehchopogh, F. S. (2024). Advances in artificial rabbits optimization: A comprehensive review. Archives of Computational Methods in Engineering, 1-36.
dc.identifier.doi10.1007/s11831-024-10202-7
dc.identifier.issn11343060
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1007/s11831-024-10202-7
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6046
dc.identifier.wosWOS:001371508400001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorAğaoğlu, Nazım
dc.institutionauthoridNazım Ağaoğlu / 0000-0002-6466-4274
dc.language.isoen
dc.publisherSpringer Science and Business Media B.V.
dc.relation.ispartofArchives of Computational Methods in Engineering
dc.relation.publicationcategoryDiğer
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectComplex optimization Problems
dc.subjectConvergence Properties
dc.subjectConvergence Rates
dc.subjectExploration and Exploitation
dc.subjectGlobal Solutions
dc.subjectLocal Optima
dc.subjectOptimisations
dc.subjectSearch Spaces
dc.subjectOptimization Algorithms
dc.titleAdvances in Artificial Rabbits Optimization: A Comprehensive Review
dc.typeOther

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